Persistent and chronic infections are maintained by a dynamic modulation of microbe - host cell interactions. During this process, microorganisms evolve and adapt to the host by regulating the expression of different genes, in particular those involved in virulence. At the bacterial population level, specific (possibly hypervirulent) clones may predominate at different times in individuals as well as groups of patients. The timely storage of microbial pathogens in the microbiology laboratory together with the availability of clinical data from the patients allows following the virulence traits, host adaptation and changing epidemiology of the pathogens. Two specific examples are summarized below: 1) We have performed extensive molecular identification and typing of 42 clinical isolates of M. abscessus and the closely related newly-described species M. massiliense and M bolletii from patients followed at the NIH between 1999 and 2007. This work lead to the identification of characteristic clonal groups for each species, including two major clonal clusters for M. abscessus and one for M. massiliense. In particular, we identified a distinct group of strains with mixed features of M. abscessus and M. massiliense. Pan-mycobacterial microarray platforms were used to reveal genomic differences among these clonal groups. More recently, we performed whole genome sequencing of the type strain of the emerging pathogen Mycobacterium massiliense in order to identify distinguishing virulence and epidemiological traits. 2) The characterization of a nosocomial outbreak of Acinetobacter baumannii in collaboration with NHGRI revealed that genome-wide recombination drives the diversification of epidemic strains of this organism. We have characterized multiple strains of multidrug resistant Klebsiella pneumoniae as an outbreak developed in our institution. Integrated genomic and epidemiological analysis traced the outbreak to three independent transmissions from a single patient who was discharged 3 weeks before the next case became clinically apparent. This work demonstrates that integration of genomic and epidemiological data can yield actionable insights and facilitate the control of nosocomial transmission.